We have automated several of our core customer service and data entry processes using AI agents. How do we track these automated processes on our weekly Level 10 Meeting™ Scorecard when there is no human directly executing the daily tasks?

Question

Tyler Smith · Accepted Answer

Just because an AI agent is executing the work does not mean the work goes unmeasured or lacks human accountability. Every metric on your Level 10 Meeting™ Scorecard must have a single human name attached to it. An AI cannot own a scorecard metric; a person on your Accountability Chart must.

Your scorecard should pivot from measuring manual human activity to measuring system performance, accuracy, and throughput.

For example, instead of tracking the number of manual emails sent by an employee, track:
- The resolution rate of your AI customer service agent
- The average cost per automated transaction
- The percentage of exceptions that require human intervention

The human owner of that scorecard metric is the leader whose seat is accountable for that operational output. If the AI agent's performance drops below the weekly target, that leader is responsible for dropping the miss to the Issues List.

During IDS®, the team will solve the systemic issue. Is the API failing? Does the prompt need refinement? Or is the data input flawed?

By tracking automated metrics on your scorecard, you maintain complete visibility over your AI-powered operations while keeping your leadership team fully accountable for the results.